학술논문

ANNs and geographical information for urban analysis evidence from the european fp7 secoa project
Document Type
TEXT
Source
Subject
Language
English
Multiple languages
Abstract
The Artificial Adaptive Systems (AAS) have had several applications in different technical and scientific fields, in medical research, life sciences, and financial and insurance studies. These systems have had, so far, poor implementation in social sciences. Among the latter, the main examples can be found in research about urban models in which AAS are usually used together with GISystems. By their nature, neural networks are suitable for interpreting complex phenomena like the social ones. Their limited use is, therefore, surprising. It is just to explain a complex phenomenon that AAS have been used in the SECOA project. The project deals with the study of environmental conflicts in coastal areas. Environmental conflicts are, by nature, complex phenomena, multidimensional and multiscalar. In SECOA 26 conflicts in 17 regions were analysed. The AAS were used to generate an explanatory model that would allow to describe, through its essential elements, the relationship between conflicts and territories. AAS are not only an ordinary complement to the spatial analysis toolbox but a new paradigm for spatial analysis and mining. In particular Geo-SOM (Geo-Self-Organizing Map) is a tool to identify homogenous regions for which predictive analysis can be done using tools that make the visualisation of positive and negative correlation possible. Increased use of AAS and GIS, and the good results this method produced, contributed to a more precise identification of a GIScience in general and its research agenda in particular.